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Courses, in 8 stages

  1. 01Programming for AI/ML9 courses
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  1. Courses
  2. Imbalanced Classification
  3. Introduction

Build and examine baseline

Video · 8 min · Lesson 3 of 26

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Machine LearningImbalanced Classification

    1. Problem with Imbalanced ClassesFree5 min
    2. ResourcesFree2 min
    3. Build and examine baselineFree8 min
    4. Download Resources1 min
    1. Approach 1: Upsampling the minority classFree7 min
    2. Approach 2: Downsampling the majority class6 min
    3. Approach 3: Cluster Centroids - TheoryFree12 min
    4. Code Demo4 min
    5. Approach 4: SMOTE Algorithm Theory6 min
    6. Code Demo7 min
    7. Approach 5: ADASYN Algorithm Theory12 min
    8. Code Demo3 min
    9. Approach 6: Near Miss6 min
    10. Approach 7: Tomek Links3 min
    11. Code Demo4 min
    12. Course Review1 min
    1. Class Sensitive Learning Theory6 min
    2. Code Demo4 min
    3. Class Weighted XGBoost and Demo8 min
    1. One Class Classification Theory4 min
    2. One Class using SVM8 min
    3. Mahalanobis Distance for One Class Classification11 min
    4. Isolation Forest Demo10 min
    5. Data Leakage - A sneaky surprisingly hard to detect example8 min
    6. Edited Nearest Neighbour based example12 min
    7. Probability Threshold Tuning11 min

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